Comparative Analysis of Image Detection Techniques

I. MEMON, S. DAHRI, F. MEMON, F. QURESHI

Abstract


Image detection is a sub field of image processing. It is used for detection of images of real world. This field has gained huge importance in last two decades because of its increasing demand especially in fields of Security, Medical, Industries, & Biometrics. This paper presents the detailed comparison & experimental analysis of six different image detection techniques (i.e., SURF, FAST, BRISK, HARRIS, MinEIGEN& MSER). Their performance is analyzed on MATLAB (2015a). For their analysis, three different Scenarios (Single image, 3-card Image & Cluttered Scene) are considered along with four cases (Simple, Rotation, Scaling, & Illumination. The accuracy of these techniques have been analyzed in each scenarios using four cases in terms of their Detected Feature Points.

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